Breadth-first search (BFS) is a core primitive for graph traversal and a basis for many higher-
level graph analysis algorithms. It is also representative of a class of parallel computations …

Data-intensive, graph-based computations are pervasive in several scientific applications,
and are known to to be quite challenging to implement on distributed memory systems. In …

With the emergence of data science, graph computing is becoming a crucial tool for
processing big connected data. Although efficient implementations of specific graph …

Many important problems in computational sciences, social network analysis, security, and
business analytics, are data-intensive and lend themselves to graph-theoretical analyses. In …

We present topic-regression multi-modal Latent Dirich-let Allocation (tr-mmLDA), a novel
statistical topic model for the task of image and video annotation. At the heart of our new …

Large, real-world graphs are famously difficult to process efficiently. Not only they have a
large memory footprint but most graph processing algorithms entail memory access patterns …

Breadth-First Search (BFS) is a core primitive for graph traversal and a basis for many higher-
level graph analysis algorithms. It is also representative of a class of parallel computations …

Graph-based structures are being increasingly used to model data and relations among
data in a number of fields. Graph-based databases are becoming more popular as a means …

Breadth-first search (BFS) is a fundamental graph primitive frequently used as a building
block for many complex graph algorithms. In the worst case, the complexity of BFS is linear …

The world of Big Data is changing dramatically right before our eyes-from the amount of data
being produced to the way in which it is structured and used. The trend of" big data growth" …